Distribution Of Mammal Species Research Articles

Bioclimatic inference based on mammal community using machine learning regression models: perspectives for paleoecological studies

Climate has played a significant role in shaping the distribution of mammal species across the world. Mammal community composition can therefore be used for inferring modern and past climatic conditions. Here, we develop a novel approach for bioclimatic inference using machine learning (ML) algorithms, which allows for accurate prediction of a set of climate variables based on the composition of the faunal community. The automated dataset construction process aggregates bioclimatic variables with modern species distribution maps, and includes multiple taxonomic ranks as explanatory variables for the predictions. This yields a large dataset that can be used to produce highly accurate predictions. Various ML algorithms that perform regression have been examined. To account for spatial dependence in our data, we employed a geographical block validation approach for model validation and selection. The random forest (RF) outperformed the other evaluated algorithms. Ultimately, we used unseen modern mammal surveys to assess the high predictive performances and extrapolation abilities achieved by our trained models. This contribution introduces a framework and methodology to construct models for developing models based on neo-ecological data, which could be utilized for paleoclimate applications in the future. The study aimed to satisfy specific criteria for interpreting both modern and paleo faunal assemblages, including the ability to generate reliable climate predictions from faunal lists with varying taxonomic resolutions, without the need for published wildlife inventory data from the study area. This method demonstrates the versatility of ML techniques in climate modeling and highlights their promising potential for applications in the fields of archaeology and paleontology.

Evolutionary history and patterns of divergence in three tropical east Asian squirrels across the Isthmus of Kra

AbstractAimUnderstanding the biotic and abiotic mechanisms underlying the generation and maintenance of biogeographic transitions represent long‐standing topics in evolutionary biology. The Isthmus of Kra (IOK) divides Sundaland and Indochina and constitutes a poorly characterized terrestrial biogeographic transition. Here we looked at population genetic structure of three species that are distributed across the IOK to gain insights into the drivers that have shaped this transition and regional diversification patterns.LocationTropical east Asia: Sundaland and Indochina.TaxaCallosciurus caniceps, Tamiops mcclellandii, and Dremomys rufigenis‐ornatus species complex (Mammalia: Rodentia: Sciuridae).MethodsWe generated complete mitogenomes and sequences of 11 nuclear intron fragments from 61 and 67 museum specimen samples, respectively. We assessed population structure by constructing Maximum Likelihood mitogenome phylogenies (IQTREE2), and nuclear marker haplowebs and conspecificity matrices (HaplowebMaker and CoMa). We estimated divergence dates through Bayesian phylogenetic inference (BEAST2) and put these results in the context of climatic and geological history.ResultsHigh levels of mitochondrial and nuclear divergence were identified across the IOK in all three squirrels. Lineage turnover was consistent with the two major mammal species distribution transitions near the Kangar‐Pattani Line and at the juncture between the Thai‐Malay peninsula and the mainland. Divergence of mitochondrial lineages across Kra was estimated in the late Pliocene/ early Pleistocene for all three taxa. Older Miocene/Pliocene divergences were estimated within Indochina in D. rufigenis‐ornatus and T. mcclellandii, which were paraphyletic.Main ConclusionsSundaic and Indochinese populations have possibly diverged in allopatric habitat refugia in or around mountains during periods of increased aridity and evergreen forest contraction. Ecological differences and/or topography might have influenced genetic differentiation during periods of rainforest expansion. Alternative hypotheses remain to be tested with more informative nuclear markers and additional geographic sampling.

Camera traps reveal the natural corridors used by mammalian species in eastern Mexico

BackgroundHabitat loss and fragmentation in the Sierra Madre Oriental (SMO) ecological corridor have negative impacts on the movement and distribution of mammalian species that are of great ecological and evolutionary importance. Part of the SMO ecological corridor that is located in the state of Hidalgo is less studied despite being a potential dispersal route for mammals. The objectives of this study were to evaluate the presence and activity of terrestrial mammals in the riparian and non-riparian zones of SMO.ResultsCamera traps detected 15 mammalian species (i.e., 14 native and 1 domestic) in the non-riparian zone, and 12 mammalian species in the riparian zone (i.e., 10 wild and 2 domestic). The riparian corridor was mainly used by opportunistic medium-sized carnivores, while large carnivores and their potential prey were more frequent in the non-riparian zone.ConclusionsOur findings suggest terrestrial mammals avoid the use of natural corridors due to the presence of domestic dogs, cattle and humans and look for new dispersal routes to move through their habitat and find the resources they need to survive. Even though some species can use disturbed corridors to move and find resources, they will change their activity patterns to avoid contact with humans and potential threats like dogs. It is, therefore, crucial to identify not one, but several corridors that must be preserved to improve the connectivity of terrestrial mammals in disturbed landscapes.

The Threat Analysis and Conservation Needs of Wild Mammals Distributing Around Van Province, Eastern Anatolian of Turkey

During the field and monitoring studies carried out in 352 different localities between 2013 and 2014, a total of 25 species were recorded by direct and indirect observation techniques in Van province in the East Anatolian Turkey. Of these, following one species (Oryctolagus cuniculus) is endangered, two species (Capra aegagrus and Ursus arctos) are vulnerable, two species (Spermophilus xanthoprymnus and Lutra lutra) are near threatened and others are least concern category according to IUCN. As a result of the findings, it was determined that rodents and carnivores have the highest rate of species in the study area and special efforts should be spent to protect important mammals in the priority areas, especially in Saray-Keçikayası, Çatak-Sak, Çatak-Dalbastı, and Gürpınar-Çepkenli villages. This dataset provides reliable records that contribute to increasing knowledge on the distribution of mammal species in Van.

Potential mammalian species for investigating the past connections between Amazonia and the Atlantic Forest.

Much evidence suggests that Amazonia and the Atlantic Forest were connected through at least three dispersion routes in the past: the Eastern route, the central route, and the Western route. However, few studies have assessed the use of these routes based on multiple species. Here we present a compilation of mammal species that potentially have dispersed between the two forest regions and which may serve to investigate these connections. We evaluate the present-day geographic distributions of mammals occurring in both Amazonia and the Atlantic Forest and the likely connective routes between these forests. We classified the species per habitat occupancy (strict forest specialists, species that prefer forest habitat, or generalists) and compiled the genetic data available for each species. We found 127 mammalian species presently occurring in both Amazonia and the Atlantic Forest for which, substantial genetic data was available. Hence, highlighting their potential for phylogeographic studies investigating the past connections between the two forests. Differently from what was previously proposed, the present-day geographic distribution of mammal species found in both Amazonia and the Atlantic Forest points to more species in the eastern portion of the dry diagonal (and adjoining forested habitats). The Central route was associated with the second most species. Although it remains to be seen how this present-day geography reflects the paleo dispersal routes, our results show the potential of using mammal species to investigate and bring new insights about the past connections between Amazonia and the Atlantic Forest.

Diversity begets diversity in mammal species and human cultures

Across the planet the biogeographic distribution of human cultural diversity tends to correlate positively with biodiversity. In this paper we focus on the biogeographic distribution of mammal species and human cultural diversity. We show that not only are these forms of diversity similarly distributed in space, but they both scale superlinearly with environmental production. We develop theory that explains that as environmental productivity increases the ecological kinetics of diversity increases faster than expected because more complex environments are also more interactive. Using biogeographic databases of the global distributions of mammal species and human cultures we test a series of hypotheses derived from this theory and find support for each. For both mammals and cultures, we show that (1) both forms of diversity increase exponentially with ecological kinetics; (2) the kinetics of diversity is faster than the kinetics of productivity; (3) diversity scales superlinearly with environmental productivity; and (4) the kinetics of diversity is faster in increasingly productive environments. This biogeographic convergence is particularly striking because while the dynamics of biological and cultural evolution may be similar in principle the underlying mechanisms and time scales are very different. However, a common currency underlying all forms of diversity is ecological kinetics; the temperature-dependent fluxes of energy and biotic interactions that sustain all forms of life at all levels of organization. Diversity begets diversity in mammal species and human cultures because ecological kinetics drives superlinear scaling with environmental productivity.

Impact of shifting cultivation on mammalian diversity and distribution in fringe areas of Dampa tiger reserve, Mizoram, India

Shifting cultivation is a largely practiced agricultural technique in the north-eastern part of India. This has led the fragmentation of natural habitat for wildlife species. Impact of jhum cultivation on distribution of mammalian species was studied through transect survey for scat, camera trapping, and burrow counting. Barking deer (27%) and wild boar (24%) were most frequent visitors. Among the carnivores highest abundance (3-5 scat samples per jhum field) was recorded for leopard cat and Indian Palm civet. 2-5 years old abandoned jhum fields were recorded to be suitable habitat for movement of large herbivores. The frequency of scat decreased with age of the jhum >5 yrs. Road sides, trails and primary forest near the active jhum forest were actively visited by clouded leopard. The encounter rate for active and old burrows of rodents were highest in 1-2 years old/ recently abandoned jhum fields with a rate of 3.56 km2 and 2.68 km2 respectively. Camera trapping also resulted in 36 images of different animal species. Increased spatial heterogeneity promotes mammalian distribution.

Assessing congruence of opportunistic records and systematic surveys for predicting Hispaniolan mammal species distributions.

Comparative assessment of the relative information content of different independent spatial data types is necessary to evaluate whether they provide congruent biogeographic signals for predicting species ranges. Opportunistic occurrence records and systematically collected survey data are available from the Dominican Republic for Hispaniola’s surviving endemic non‐volant mammals, the Hispaniolan solenodon (Solenodon paradoxus) and Hispaniolan hutia (Plagiodontia aedium); opportunistic records (archaeological, historical and recent) exist from across the entire country, and systematic survey data have been collected from seven protected areas. Species distribution models were developed in maxent for solenodons and hutias using both data types, with species habitat suitability and potential country‐level distribution predicted using seven biotic and abiotic environmental variables. Three different models were produced and compared for each species: (a) opportunistic model, with starting model incorporating abiotic‐only predictors; (b) total survey model, with starting model incorporating biotic and abiotic predictors; and (c) reduced survey model, with starting model incorporating abiotic‐only predictors to allow further comparison with the opportunistic model. All models predict suitable environmental conditions for both solenodons and hutias across a broadly congruent, relatively large area of the Dominican Republic, providing a spatial baseline of conservation‐priority landscapes that might support native mammals. Correlation between total and reduced survey models is high for both species, indicating the substantial explanatory power of abiotic variables for predicting Hispaniolan mammal distributions. However, correlation between survey models and opportunistic models is only moderately positive. Species distribution models derived from different data types can provide different predictions about habitat suitability and conservation‐priority landscapes for threatened species, likely reflecting incompleteness and bias in spatial sampling associated with both data types. Models derived using both opportunistic and systematic data must therefore be applied critically and cautiously.

Combining camera‐trap surveys and hunter interviews to determine the status of mammals in protected rainforests and rubber plantations of Menglun, Xishuangbanna, SW China

AbstractHunting and deforestation are the two biggest threats to vertebrates in Southeast Asia. In the last 50 years, monoculture rubber plantations replaced large areas of tropical rainforests in Xishuangbanna, southwest China. We set up camera traps at 109 stations (57 in forest reserves and 52 in rubber plantations) to determine the distribution of mammal species in Menglun, Xishuangbanna. We also interviewed 37 experienced hunters (mean age: 54) in the study area to understand their perceptions of species abundance trends. We used hierarchical multispecies occupancy modelling to determine the effect of distance to village, distance to forest edge and elevation on mammal occupancy after accounting for imperfect detection. We used non‐parametric tests for the rank data to evaluate perceived species trends. Using a combination of historical literature (1954–1985), hunter interviews, direct observations and camera‐trap surveys, we only recorded 56% (15 out of 27) of the medium‐to‐large sized (>1 kg) mammal species known previously from the study region. Interviews suggested that current population densities of all extant mammal species are below historical levels. Our camera traps captured 11 mammal species in the forest reserve and only two species in rubber plantations. Low capture rates (10 captures) in rubber mean we could only determine mammal occupancy in forests. Environmental variables did not affect community level mammal occupancy in forests, but common muntjac (Muntiacus muntjak) and the northern pig‐tailed macaque (Macaca leonina) avoided forest edges. At the time of the survey, hunting was still prevalent in the region. Therefore, conservation interventions that end both hunting and deforestation are urgently needed to stabilize and increase mammal populations in the region.

Variation in behavioral traits of two frugivorous mammals may lead to differential responses to human disturbance.

Human activities can lead to a shift in wildlife species’ spatial distribution. Understanding the specific effects of human activities on ranging behavior can improve conservation management of wildlife populations in human‐dominated landscapes. This study evaluated the effects of forest use by humans on the spatial distribution of mammal species with different behavioral adaptations, using sympatric western lowland gorilla and central chimpanzee as focal species. We collected data on great ape nest locations, ecological and physical variables (habitat distribution, permanent rivers, and topographic data), and anthropogenic variables (distance to trails, villages, and a permanent research site). Here, we show that anthropogenic variables are important predictors of the distribution of wild animals. In the resource model, the distribution of gorilla nests was predicted by nesting habitat distribution, while chimpanzee nests were predicted first by elevation followed by nesting habitat distribution. In the anthropogenic model, the major predictors of gorilla nesting changed to human features, while the major predictors of chimpanzee nesting remained elevation and the availability of their preferred nesting habitats. Animal behavioral traits (body size, terrestrial/arboreal, level of specialization/generalization, and competitive inferiority/superiority) may influence the response of mammals to human activities. Our results suggest that chimpanzees may survive in human‐encroached areas whenever the availability of their nesting habitat and preferred fruits can support their population, while a certain level of human activities may threaten gorillas. Consequently, the survival of gorillas in human‐dominated landscapes is more at risk than that of chimpanzees. Replicating our research in other sites should permit a systematic evaluation of the influence of human activity on the distribution of mammal populations. As wild animals are increasingly exposed to human disturbance, understanding the resulting consequences of shifting species distributions due to human disturbance on animal population abundance and their long‐term survival will be of growing conservation importance.

Modeling current and potential distributions of mammal species using presence-only data: A case study on British deer.

AimDecisions on wildlife conservation, management, and epidemiological risk are best based on robust evidence. The continual improvement of species distributions, such that they can be relied upon in decision‐making, is important. Here we seek to refine aspects of a generic modelling approach and improve the utility of species distribution maps.LocationGreat Britain (GB).MethodsWe applied a modeling framework based on hierarchical Bayesian species distribution models exploiting opportunistic occurrence records from citizen science datasets to predict both current and potential distributions for each of the six deer species known to be present in GB. Using the resulting maps, we performed a simple analysis of the overlap between species to illustrate possible contact, which we interpret as the relative risk of potential disease spread given an introduction.ResultsPredicted distribution maps showed good agreement with the broader scale occurrence reported by a recent national deer survey with an average True Skill Statistics and AUC of 0.69 and 0.89, respectively. Aggregation of the maps for all species highlighted regions of central and eastern England as well as parts of Scotland where extensive areas of range overlap could result in interspecific contact with consequences for risk assessments for diseases of deer. However, if populations are allowed to expand to their predicted potential, then areas of overlap, and therefore disease interspecific transmission risk, will become extensive and widespread across all of mainland Britain.Main conclusionsThe generic modeling approach outlined performed well across all of the deer species tested, offering a robust and reliable tool through which current and potential animal distributions can be estimated and presented. Our application, intended to inform quantitative risk assessments, demonstrates the practical use of such outputs to generate the valuable evidence required to inform policy decisions on issues such as management strategy.

Insights on the role of forest cover and on the changes in forest cover on thirty-five endangered mammal species distributions

Abstract The changes in forest cover can determine the survival of terrestrial endangered mammal species in the wild. This study assessed the impacts of forest cover changes on endangered mammal species distribution at global scale aiming to understand how the changes in forest cover may have impacted the distributions of 35 endangered small and large-body terrestrial mammals. There were used forest data obtained from time-series analyses of Landsat images between 2000 and 2014, species occurrence records collected by observations between 2000 and 2015 of Global Biodiversity Information Facility and species range data of International Union for Nature Conservation (IUCN) of the year 2015, to test the ‘natural and resource conditions’ hypothesis. Hypothesis on ‘natural and resource conditions’ produced models with high prediction accuracy of above 70 percent for 88 percent of 35 species models. The changes in forest cover explained species occurrences in 10 percent of all species models. In average, 59 percent of species occurrence records overlapped with species range data. The 51 percent of all species had no occurrence records between 2000 and 2015. Species and forest data collection as well as transnational cooperation for conservation of species roaming in the wild in upland forested areas and in cross-border areas may be critical for endangered mammal species conservation.

Modeling endangered mammal species distributions and forest connectivity across the humid Upper Guinea lowland rainforest of West Africa

Species distribution data provide critical baseline information for conservation planning and decision making. However, in many of the Earth’s most biodiverse regions, such data are lacking for many species. Here, we used ecological niche modeling and connectivity analyses to model distributions of endangered species and protected area connectivity across the Upper Guinea Forest (UGF) Global Conservation Hotspot of West Africa. We estimated the current distributions of African forest elephant Loxodonta cyclotis (Vulnerable), western chimpanzee Pan troglodytes verus (Critically Endangered), and pygmy hippopotamus Choeropsis liberiensis (Endangered) across the region and optimized connectivity in two main forest complexes in the region. We used occurrence data for the period 2010–2016 for the three species from two well-sampled national parks in Liberia (Sapo National Park and Gola National Park), and remotely sensed MODIS enhanced vegetation index data for the period 2010–2015. Our models predicted a total of 75,157 km2 of suitable habitat for chimpanzees in the region, 79,400 km2 for elephants, and 290,696 km2 for hippos. Of these areas, for chimpanzees, 30% of the area predicted falls within the boundaries of proposed or designated protected areas, and likewise 30% for elephants, and 19% for hippos. Liberia had the largest blocks of contiguous forest suitable for these species compared to other countries in the region but this forest was largely unprotected. This study identifies priority areas for biodiversity conservation and forest connectivity in the region, and reemphasizes the practicality of these tools to optimize conservation planning and implementation.

Niche modelling of the potential distribution of the Egyptian Vulture Neophron percnopterus during summer and winter in Iran, to identify gaps in protected area coverage

SummaryAn analysis of the extent of overlap between habitats of the Egyptian Vulture Neophron percnopterus during summer and winter in Iran, and Iranian protected areas, discovered slight overlap between the two. Our study aimed to survey suitable habitats of the Egyptian Vulture during summer and winter in Iran using MaxEnt, a species distribution modelling method, and compare the results with the locations and span of protected areas. Model fitness was assessed using the area under the ROC-plot and True Skill Statistics. We found that habitat suitability in Iran varies for the Egyptian Vulture during summer and winter. Summer visitors are scattered in the north and west of Iran, concentrated along the Zagros and Alborz mountain ranges. Winter visitors and residents are scattered in coastal areas in the south. Habitat protection for winter visitors was the greatest, with 10% of suitable habitat covered, while less than 10% of suitable habitat for residents and summer visitors fell within protected areas. The Egyptian Vulture is categorised as ‘Endangered’ on the IUCN Red List. Different environmental factors influence the suitability of habitat for the species. While some factors such as NDVI and anthropogenic disturbance influence all visitors in a similar way, the effects of others such as elevation and distance from protected areas vary for summer and winter visitors. Since designation of protected areas in Iran is mainly determined by the distribution of mammal species, protection of bird habitats is often overlooked. Suitable habitat for the species should be considered when selecting protected areas in future.

Improving performance and transferability of small mammal species distribution models

ABSTRACTIn theory, interpretation and transferability of species distribution models (SDMs) should be improved by including abiotic and biotic factors that directly influence a species’ fundamental niche. We investigated whether adding topographic, soil and vegetation variables to a climate-only model improved model performance and predictive capacity for four coastal small mammal species. Adding landscape variables improved the structural goodness of fit for all four species (e.g. 2.6–47.6% increase in deviance explained), and the information-theoretic rankings (based on AICc, BIC and DIC) for the wet-heath specialist (Muridae, Rattus lutreolus lutreolus) and peramelid (Peramelidae, Isoodon obesulus obesulus). For the latter species, improved model performance successfully coincided with improved predictive capacity in the out-of-region validation (increase in the area under the curve, AUC). However, this result was poorly supported by trends in the successful classification of absences (specificity) indicating a modelling bias caused by low prevalence of species occurrence. Across all SDMs, additional abiotic and biotic landscape variables contributed between 3.7 and 14.9% of accumulative deviance explained. Our results illustrate increased model fit and transferability for select species, highlighting the potential for landscape variables that represent resources to better represent the fundamental niche in SDMs.

Multi-scale dynamic maps for the management of invading and established wildlife populations: brushtail possums in New Zealand

Context The abundance and distribution of mammalian species often change in response to environmental variability, losses or gains in suitable habitat and, in the case of pest species, control programs. Consequently, conventional distribution maps rapidly become out of date and fail to provide useful information for wildlife managers. For invasive brushtail possum populations in New Zealand, the main causes of change are control programs by central and local government agencies, and post-control recovery through recolonisation and in situ recruitment. Managers need to know current, and likely future, possum population levels relative to control targets to help assess success at preventing the spread of disease or for protecting indigenous species. Information on the outcomes of government-funded possum control needs to be readily available to members of the general public interested in issues such as conservation, disease management and animal welfare. Aims To produce dynamic, scalable maps of the current and predicted future distribution and abundance of possums in New Zealand, taking into account changes due to control, and to use recent visualisation technology to make this information accessible to managers and the general public for assessing control strategies at multiple spatial scales. Methods We updated an existing individual-based spatial model of possum population dynamics, extending it to represent all individuals in a national population of up to 40 million. In addition, we created a prototype interface for interactive web-based presentation of the model’s predictions. Key results The improved capability of the new model for assessing possum management at local-to-national scales provided for real-time, mapped updates and forecasts of the distribution and abundance of possums in New Zealand. The versatility of this platform was illustrated using scenarios for current and emerging issues in New Zealand. These are hypothetical incursions of possums, reinvasion of large areas cleared of possums, and impacts on animal welfare of national-scale management of possums as vectors of bovine tuberculosis (TB). Conclusions The new individual-based spatial model for possum populations in New Zealand demonstrated the utility of combining models of wildlife population dynamics with high-speed computing capability to provide up-to-date, easily accessible information on a species’ distribution and abundance. Applications include predictions for future changes in response to incursions, reinvasion and large-scale possum control. Similar models can be used for other species for which there are suitable demographic data, typically pest species, harvested species or species with a high conservation value. Implications Models such as the spatial model for possums in New Zealand can provide platforms for (1) real-time visualisation of wildlife distribution and abundance, (2) reporting and assessing progress towards achieving management goals at multiple scales, (3) use as a decision-support tool to scope potential changes in wildlife populations or simulate the outcomes of alternative management strategies, and (4) making information about pest control publicly available.

Regional zoogeographical zoning using species distribution modelling by the example of small mammals of South-Eastern Transbaikalia

Zoogeographical studies of regional scale always deal with incompleteness of faunal information. Such information is usually available as a set of localities, covering the studied area as an irregular network. At the same time, full coverage of data is needed for any spatial analysis. In this study, we attempted to perform faunal zoning at a regional level, formalising the procedure to the greatest extent possible. We used 47 small mammal species distribution models (SDM) as initial data for faunal zoning. SDMs were previously constructed based on localities determined using museum labels and environmental data with the maximum entropy method. SDMs were converted to binary values using fixed threshold. We calculated 1-Jaccard similarity coefficients between unique sets of predicted species compositions in each raster cell. The resulting dissimilarity matrix was analysed using hierarchical cluster analysis with the Ward and unweighted average methods. We distinguished three large clusters with nine subclusters based the similarity of the fauna composition. Patterns of the spatial distribution of species numbers and species composition homogeneity were obtained. The relationships between the distribution of species richness and the spatial heterogeneity of the fauna with latitude, longitude, altitude and environmental factors were studied using regression and discriminant analysis. Finally, two faunas were found in South-Eastern Transbaikalia, and a large territory in this region is occupied by a zone of their interpenetration. Analysis of stacked SDMs proposed as important tool for investigation of regional zoogeographical heterogeneity. It is especially useful for extrapolation of faunal data to a larger unstudied territory.

Detecting and attributing the effect of climate change on the changes in the distribution of Qinghai-Tibet plateau large mammal species over the past 50 years

The effects of prior climate change on large mammal distributions are uncertain. We evaluated the relationship between the changes in the distribution of Qinghai-Tibet plateau large mammals and climate change over the past 50 years and examined whether these changes can be attributed to climate change in China. Long-term distribution records of mammal species, grey relational analyses, the fuzzy-set classification technique, the consistency index, and attribution methods were used. Over the past 50 years, the mammal distributions have primarily shifted eastward or westward, and most of these changes are correlated with the thermal index. In response to climate change over the past years, the distribution boundary and the distribution center of particular species have changed and have exhibited fluctuations. The observed and predicted changes in the distributions were highly consistent for certain species. The changes in the southern limit, western limit, or center latitude of the distribution of some mammal species can be attributed to climate change.

Neotoma: A Programmatic Interface to the Neotoma Paleoecological Database

Paleoecological data are integral to ecological and evolutionary analyses. First, they provide an opportunity to study ecological and evolutionary interactions between communities and abiotic environments across time scales. Second, they allow us to study the long-term outcomes of processes that occur infrequently, such as megadroughts, hurricanes, and rapid climate change. Third, the past allows us to study ecological processes in the absence of widespread anthropogenic influence. The R package neotoma, described here, obtains and manipulates data from the NeotomaPaleoecological Database (Neotoma Database: http://www.neotomadb.org ). The Neotoma Database is a public-domain searchable repository for multiproxypaleoecological records spanning the past 5 million years. The Neotoma Database provides the data and cyberinfrastructure to study spatiotemporal dynamics of species and communities from the Pliocene to the present; neotoma provides a user interface to enable these studies. neotoma searches the Neotoma Database using terms that can include location, taxon name, or dataset type (e.g., pollen, vertebrate fauna, ostracode) using the Database’s Application Programming Interface (API). The package returns a set of nested metadata associated with the site, including the full assemblage record, geochronological data to enable the rebuilding of age models, dataset metadata (e.g. age range of samples, date of accession into Neotoma, principal investigator), and site metadata (e.g. location, site name and description). neotoma also provides tools to allow cross-site analysis, including the ability to standardize taxonomies using built-in taxonomies derived from the published literature or user-provided taxonomies. We show how key functions in the neotoma package can be used, by reproducing analytic examples from the published literature focusing on Pinus migration following deglaciation and shifts in mammal species distributions during the Pleistocene.

Assessing potential effects of land use and climate change on mammal distributions in northern Thailand

Context Tropical ecosystems are widely recognised for their high species richness and outstanding concentrations of rare and endemic species. Previous studies either focussed on the effects of deforestation or climate change, whereas studies on the combined effects of these two major threats are limited. Aims This research aimed to model current and future distributions of medium- to large-sized mammal species on the basis of different land-use and climate-change scenarios in 2050 and to assess whether the predicted effects of land-use change are greater than those of climate change and whether the combined effects of these drivers are greater than those of either individual driver. Methods The present article demonstrates a method for combining nationwide wildlife-inventory data, spatially explicit species-distribution models, current and predicted future bioclimatic variables, other biophysical factors and human disturbance to map distributions of mammal species on the basis of different land-use and climate-change scenarios and to assess the role of protected areas in conservation planning. Key results Seventeen medium- to large-sized mammal species were selected for modelling. Most selected species were predicted to lose suitable habitat if the remaining forest cover declines from the current level of 57% to 50% in 2050. The predicted effects of deforestation were stronger than the effects of climate change. When climate and land-use change were combined, the predicted impacts were more severe. Most species would lose suitable habitat and the average shift in species distribution was greater than 40%. Conclusions The predicted effects were positive for only a few species and negative for most species. Current and future centres of mammal-species richness were predicted in large and contiguous protected forests and the average contribution of existing and proposed protected areas in protecting the focal species will increase from 73% to 80% across all scenarios. Implications The present research advances the current understanding of the ecology of 17 medium- to large-sized mammal species with conservation relevance and the factors that affect their distributions at the landscape scale. In addition, the research demonstrated that spatially explicit models and protected areas are effective means to contribute to protection of mammal species in current and future land-use and climate-change scenarios.